Production Support Engineer Cloud in United States

Locations: South Jordan, UT Salary: $56,000 Launch Your Career in Technology Every app, website, payment, and digital service relies on technology running smoothly behind the scenes. When something goes wrong, Production Support Engineers are the people who investigate the issue, restore service, and help prevent it from happening again. If you're curious, analytical, and enjoy solving problems, this is an opportunity to build hands-on experience with cloud platforms, Linux, automation, databases, and large-scale enterprise systems from day one. What Is Production Support? Production Support Engineers keep business-critical applications running reliably in live environments. Think of it this way: Software Engineers build the platform. QA Engineers test the platform. Production Support Engineers keep the platform running when it matters most. Working at the intersection of technology and business, you'll troubleshoot issues, automate processes, and help improve the reliability and performance of systems used by thousands, or even millions, of people every day. If you enjoy solving puzzles, working under pressure, and understanding how large-scale systems work, this could be the perfect place to start your career. What You'll Do As part of a global production engineering team, you'll: Help support large-scale applications and platforms used by leading organizations around the world. Monitor business-critical applications and services to ensure high availability and performance. Investigate and resolve production incidents across applications, infrastructure, databases, and cloud environments. Analyse logs, alerts, and system metrics to identify root causes and prevent recurring issues. Partner with software engineers, infrastructure teams, and business stakeholders to improve system reliabilit

Datadog’s Cloud Networks team designs, builds, and maintains the production network infrastructure that powers everything built on top of our platform across AWS, GCP, Azure, and beyond. In this role, you’ll set technical direction for how we scale our multi-region, multi-cloud network footprint while keeping reliability and performance high. You’ll partner closely with internal teams and Cloud Service Providers to troubleshoot complex connectivity issues, integrate new networking capabilities, and improve the foundations our engineers and customers rely on. This is a high-impact opportunity to drive meaningful improvements in scale, resiliency, and cost efficiency. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design, build, and operate cloud network infrastructure across AWS, GCP, Azure, and Neoclouds in a multi-region environment. Own connectivity between clouds, customers, and developers—ensuring scalable, secure, and reliable network paths. Set clear technical direction for expanding data centers and evolving the network while maintaining stability and performance. Improve cross-site and cross-region connectivity patterns to support Datadog’s growing platform needs. Lead deep investigations into latency, packet loss, and connectivity failures – from pcap and path analysis through to escalations with cloud providers that may originate from customer support Identify and deliver network-related efficiency and cost-saving opportunities that positively impact business health. Who You Are: You have deep networking expertise. You understand BGP, route policies, path selection, prefix advertisement, and what breaks in large-scale networking. You have substantial experience designing, building, and evolving large-scale Software-Defined Networks—inclu

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Cloud Platform Engineer, you'll envision and build robust systems and processes that ensure our infrastructure is scalable, reliable, and efficient. This can range from automating deployments and monitoring systems to optimizing performance and managing incidents. We all work closely with our users, learning from their past struggles in operationalizing ML, onboarding them onto our platform, and turning our learnings into ideas for improving Baseten. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Build and maintain scalable infrastructure to support the deployment and operation of machine learning models. Establish standards and best practices for reliability and performance across the infrastructure. Automate processes when relevant, particularly for managing CI/CD pipelines. Own products and projects end-to-end, functioning as both an engineer and a project manager, with a focus on user empathy, project specification, and end-to-end execution. Collaborate with cross-functional teams to understand project requirements and translate them into technical solutions. Mentor junior team members and contribute to knowledge sharing within the organization. Navigate ambiguity and exercise good judgment on tradeoffs and

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi

About the Role We are seeking a Cloud Infrastructure Engineer to help design and evolve the platforms that power OpenAI’s products. In this role, you will be a hands-on technical leader, driving the architecture, scalability, reliability, and security of critical infrastructure systems. You will help define how we build and operate infrastructure at the next order of magnitude, while influencing technical direction across teams. This role is both deeply technical and highly strategic, requiring strong ownership, sound judgment, and the ability to partner effectively across engineering, product, and research organizations. In this role, you will: Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products Evolve cloud infrastructure abstractions that enable rapid product development across teams Architect systems to support significant growth, performance, and operational complexity Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture Influence technical direction and infrastructure strategy across multiple teams Partner closely with product, research, and engineering teams to align infrastructure with evolving needs Own operational excellence, including participation in on-call rotations, incident response, and production readiness Mentor engineers and raise the overall technical bar of the organization Contribute to a culture of high ownership, low ego, and thoughtful collaboration You might thrive in this role if you: 8+ years of experience building and operating large-scale infrastructure systems Deep expertise in Kubernetes and container orchestration at scale Strong experience designing cloud abstractions and platform infrastructure (AWS, GCP, Azure, or similar) Proven track record of leading complex technical initiatives across teams Experience operating highly reliable, secure, and scalable distributed systems Security engineering experience or security backgroun

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: 5+ years of engineering experience running production infrastructure at a large scale Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters Experience with Kubernetes dev and production coding and support Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving Experienc

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely depl

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations Austin, US About the Role Cloudflare's People team supports 5,000+ employees globally. To scale, we are building an AI-driven operating layer on the Cloudflare Developer Platform to automate workflows, ensure data integrity, and streamline employee support. You will ship production systems for hiring, onboarding, and self-service, using AI to create leverage while designing rigorous guardrails for sensitive employee data. Lever

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Observe by Snowflake is a high-growth SaaS observability platform built on the Snowflake AI Data Cloud, enabling businesses to troubleshoot modern distributed applications 10x faster. Now, as a core part of Snowflake, we’ve reached a major milestone in the evolution of the Snowflake platform. By bringing AI-powered observability directly into the Snowflake ecosystem, we’ve created the first truly unified platform for telemetry and business data. We’re looking for an Implementation Engineer to help enterprise customers successfully deploy, configure, and operationalize Observe. This is a hands-on, post-sales technical role focused on delivering strong first outcomes, accelerating time-to-value, and establishing a solid foundation for long-term customer success. Implementation Engineers are deeply technical, customer-facing practitioners who work closely with customer platform, SRE, DevOps, and application teams during onboarding and early adoption. In this role, you’ll translate existing observability architectures (including OpenTelemetry-based pipelines, Splunk, ELK, and other monitoring solutions) into scalable, production-ready implementations on Observe—using best practices while balancing speed, quality, and customer enablement. Implementation Engineers focus on initia

NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. We are seeking a hands-on, platform-minded engineer to build and evolve the systems that turn distributed infrastructure telemetry and operational data into reliable, governed data products. You will work across ingestion, transformation, data quality, platform architecture, security, observability, and self-service consumption to help make Navigator and the DGXC data platform a dependable source of truth. We do expect strong engineering fundamentals, experience operating production systems, and the ability to learn new platforms and domains quickly. What you'll be doing: Own systems end to end. For example, work from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support. Construct data pipelines and products. Such as designing and maintain batch and streaming ingestion, transformation, reconciliation, and serving paths for fleet, capacity, utilization, cost, scheduling, and operational telemetry. Build shared libraries, workflow and DAG or equivalent experience abstractions to evolve the data platform. Develop deployment tooling, data

NVIDIA is hiring an NCX Senior Engineer who is passionate about NVIDIA Cloud Partner (NCP) infrastructure operations to join our DSX team. This role involves working closely with strategic NVIDIA Cloud Partners to build and improve the operational capabilities essential for running large-scale NVIDIA accelerated infrastructure reliably in production. Your role involves guiding partners beyond the initial cluster deployment and validation phase into advanced Day 2 operations. These operations cover ongoing infrastructure health, observability, lifecycle management, quick remediation, performance validation, and operational readiness. You will engage directly with partner engineering and operations teams to develop consistent approaches that support NVIDIA workloads and the broader external customer environments of the partners. This is a highly technical, hands-on role at the intersection of NVIDIA accelerated computing, cloud infrastructure, distributed systems, and production operations. What you'll be doing: Lead NCP Day 2 operational readiness efforts. Collaborate directly with NVIDIA Cloud Partners to set up the systems, procedures, automation, and operational methods necessary to consistently manage NVIDIA accelerated infrastructure following initial deployment and activation. Build continuous infrastructure validation. Develop and implement methods to continuously validate GPU, CPU, storage, and network health. Do this across large-scale AI clusters to identify degraded infrastructure before it impacts critical training or inference workloads. Establish observability and operational telemetry. Help NCPs implement comprehensive telemetry, monitoring, alerting, dashboards, and operational signals across compute, GPU, InfiniBand/RoCE networking, storage, Kubernetes, and AI workloads. Devel

About the Team Security is foundational to OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security organization protects OpenAI’s technology, people, and products by building and operating deeply technical systems that must work reliably at massive scale. Our work underpins OpenAI’s commitments around safety, privacy, and security across research, products, and emerging platforms. The Host Assurance team exists to make bare metal and VMs dependable & scalable foundations for OpenAI: secure by default, verifiable in practice, and resilient across providers and operating models. We operate at the trust boundary between hardware and cloud-scale orchestration, ensuring that hosts are eligible to safely run workloads with predictable security properties and auditability. About the Role OpenAI is seeking a Software Engineer, Host Assurance to build and operate the services, APIs, and host software that establish and maintain trust in our compute infrastructure. You will own production software from design and implementation through testing, rollout, observability, and operation. Your work will support capabilities such as machine identity, certificate issuance and enrollment, secure bootstrap, and host attestation across bare-metal and VM environments. Success in this role requires strong technical judgment, the ability to reason across software and host-system boundaries and learn unfamiliar parts of the stack, and a practical mindset for building systems that are secure, reliable, and usable in fast-moving production environments. The systems you build will sit on the critical path of OpenAI’s frontier infrastructure investments and will directly shape how large amounts of compute are brought online - securely, responsibly, and at global scale - underpinning long-lived commitments around privacy, security, and reliability. You will partner closely with infrastructure, research, and confidential computing initiatives—inc

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. What You'll Do: Platform & Runtime Security Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) Strengthen boundaries between customers, workloads, and internal systems Identify and mitigate risks in distributed, dynamic compute environments Container &

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads